February 16, 2021
I start the work with the data by finding the differentially expressed genes.
To do so, I perform the tests for comparison of the means of control and disease groups, starting with simple two sample for t-test. For each gene I also check the variances equality before comparing the groups’ means.
The number of differentiated genes proved to be really high, therefore I check whether the assumption on the normality of the distribution does not hinder the results by applying new test scheme:
I compare the result of taking the distribution into consideration with the previous assumption.
After getting gene differentiation, I proceed with enrichment analysis. I will start with ORA, then proceed into FCS methods.
## Title corrected_pvals ## 100 RNA transport 4.259285e-08 ## 133 Cell cycle 4.259285e-08 ## 305 MicroRNAs in cancer 1.182302e-07 ## 260 Alzheimer disease 1.960257e-06 ## 265 Prion disease 1.960257e-06 ## 295 Human T-cell leukemia virus 1 infection 1.960257e-06 ## 300 Pathways in cancer 2.529952e-06 ## 88 Metabolic pathways 4.283633e-06 ## 263 Huntington disease 4.283633e-06 ## 266 Pathways of neurodegeneration - multiple diseases 4.546480e-06 ## 115 Fanconi anemia pathway 6.612935e-06 ## 170 Focal adhesion 6.612935e-06 ## 304 Proteoglycans in cancer 6.612935e-06 ## 262 Amyotrophic lateral sclerosis 7.685330e-06 ## 101 mRNA surveillance pathway 2.554206e-05
## Title corrected_pvals ## 88 Metabolic pathways 2.368986e-08 ## 133 Cell cycle 2.368986e-08 ## 300 Pathways in cancer 2.368986e-08 ## 295 Human T-cell leukemia virus 1 infection 4.941884e-08 ## 170 Focal adhesion 1.231707e-07 ## 305 MicroRNAs in cancer 5.131701e-07 ## 159 Vascular smooth muscle contraction 5.800451e-07 ## 116 MAPK signaling pathway 2.139096e-06 ## 119 Rap1 signaling pathway 2.139096e-06 ## 125 Chemokine signaling pathway 4.895844e-06 ## 304 Proteoglycans in cancer 4.895844e-06 ## 148 PI3K-Akt signaling pathway 5.527751e-06 ## 144 Endocytosis 5.931361e-06 ## 177 Complement and coagulation cascades 5.931361e-06 ## 121 cGMP-PKG signaling pathway 7.034663e-06
## Title corrected_pvals ## 88 Metabolic pathways 9.001854e-28 ## 300 Pathways in cancer 1.231452e-22 ## 266 Pathways of neurodegeneration - multiple diseases 9.693740e-16 ## 295 Human T-cell leukemia virus 1 infection 1.234043e-15 ## 148 PI3K-Akt signaling pathway 2.047843e-14 ## 116 MAPK signaling pathway 6.369432e-14 ## 133 Cell cycle 6.369432e-14 ## 170 Focal adhesion 6.369432e-14 ## 260 Alzheimer disease 2.115722e-13 ## 305 MicroRNAs in cancer 3.002434e-13 ## 304 Proteoglycans in cancer 4.702153e-13 ## 265 Prion disease 3.590622e-12 ## 263 Huntington disease 4.907427e-12 ## 119 Rap1 signaling pathway 6.906820e-12 ## 294 Human papillomavirus infection 5.373930e-11
We can see the matlab output is definitely strange.
## P-value: 4.997284e-42
## Correlation coefficient: -0.6518573
## P-value: 0.261582
## Correlation coefficient: 0.06141717
## P-value: 2.1936e-26
## Correlation coefficient: -0.5360192
## P-value: 0.007659464
## Correlation coefficient: 0.1452507
## Title corrected_pvals ## 56 Glycerophospholipid metabolism 9.275123e-53 ## 171 ECM-receptor interaction 9.405913e-53 ## 238 Insulin resistance 1.147170e-52 ## 233 Relaxin signaling pathway 8.115912e-52 ## 240 AGE-RAGE signaling pathway in diabetic complications 9.085146e-52 ## 88 Metabolic pathways 5.763372e-51 ## 148 PI3K-Akt signaling pathway 6.818963e-51 ## 27 Arginine and proline metabolism 1.392011e-50 ## 254 Protein digestion and absorption 1.478016e-50 ## 305 MicroRNAs in cancer 1.478016e-50 ## 235 Parathyroid hormone synthesis, secretion and action 1.543308e-50 ## 173 Adherens junction 2.323504e-50 ## 273 Vibrio cholerae infection 2.323504e-50 ## 144 Endocytosis 3.092973e-50 ## 166 Apelin signaling pathway 3.250911e-50
## Title corrected_pvals ## 159 Vascular smooth muscle contraction 1.514201e-41 ## 178 Platelet activation 3.632513e-41 ## 228 Oxytocin signaling pathway 4.745869e-38 ## 231 Renin secretion 2.135954e-37 ## 166 Apelin signaling pathway 2.934893e-37 ## 131 Phospholipase D signaling pathway 4.966612e-35 ## 121 cGMP-PKG signaling pathway 5.562491e-35 ## 119 Rap1 signaling pathway 1.047192e-34 ## 109 PPAR signaling pathway 1.069441e-33 ## 230 Regulation of lipolysis in adipocytes 2.691752e-32 ## 118 Ras signaling pathway 1.665631e-31 ## 185 C-type lectin receptor signaling pathway 1.665631e-31 ## 116 MAPK signaling pathway 2.880683e-31 ## 211 Long-term depression 1.213920e-30 ## 204 Neurotrophin signaling pathway 2.380521e-30
## ORA CERNO Z PLAGE LFC LFC_abs S2N S2N_abs GSVA ## enriched gene sets 114 200 263 338 0 0 1 1 267
Absolute signal to noise: MicroRNAs in cancer
Signal to noise: cGMP-PKG signaling pathway
## Number of joint enriched gene sets: 101
## Title pval_combined ## 88 cGMP-PKG signaling pathway 0.000000e+00 ## 253 MicroRNAs in cancer 0.000000e+00 ## 249 Pathways in cancer 1.584990e-55 ## 121 Vascular smooth muscle contraction 1.472594e-50 ## 132 Focal adhesion 2.176197e-49 ## 86 Rap1 signaling pathway 3.639168e-48 ## 83 MAPK signaling pathway 7.100317e-48 ## 252 Proteoglycans in cancer 3.974759e-47 ## 140 Platelet activation 1.954365e-46 ## 99 Cell cycle 3.033170e-45 ## 194 AGE-RAGE signaling pathway in diabetic complications 1.031549e-43 ## 245 Human T-cell leukemia virus 1 infection 1.504357e-42 ## 108 Endocytosis 1.713326e-42 ## 136 Tight junction 2.279999e-42 ## 85 Ras signaling pathway 1.532563e-41